Finite Mixture of Skewed Distributions /

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Bibliographic Details
Author / Creator:Dávila, Víctor Hugo Lachos, author.
Imprint:Cham, Switzerland : Springer, [2018]
Description:1 online resource : illustrations
Language:English
Series:Springer briefs in statistics. ABE
SpringerBriefs in statistics. ABE.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11737411
Hidden Bibliographic Details
Other authors / contributors:Cabral, Celso Rômulo Barbosa, author.
Zeller, Camila Borelli, author.
ISBN:9783319980294
3319980297
9783319980287
3319980289
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (EBSCO, viewed November 15, 2018).
Summary:This book presents recent results in finite mixtures of skewed distributions to prepare readers to undertake mixture models using scale mixtures of skew normal distributions (SMSN). For this purpose, the authors consider maximum likelihood estimation for univariate and multivariate finite mixtures where components are members of the flexible class of SMSN distributions. This subclass includes the entire family of normal independent distributions, also known as scale mixtures of normal distributions (SMN), as well as the skew-normal and skewed versions of some other classical symmetric distributions: the skew-t (ST), the skew-slash (SSL) and the skew-contaminated normal (SCN), for example. These distributions have heavier tails than the typical normal one, and thus they seem to be a reasonable choice for robust inference. The proposed EM-type algorithm and methods are implemented in the R package mixsmsn, highlighting the applicability of the techniques presented in the book. This work is a useful reference guide for researchers analyzing heterogeneous data, as well as a textbook for a graduate-level course in mixture models. The tools presented in the book make complex techniques accessible to applied researchers without the advanced mathematical background and will have broad applications in fields like medicine, biology, engineering, economic, geology and chemistry.--
Other form:Print version: Dávila, Víctor Hugo Lachos. Finite Mixture of Skewed Distributions. Cham, Switzerland : Springer, [2018] 3319980289 9783319980287
Standard no.:10.1007/978-3-319-98029-4